In the field of Intelligent Transportation Systems, a key role is played by efficient route planning services. Such systems have been evolving rapidly, but they still have some restricting drawbacks, such as the lack of a full support of real-time traffic monitoring and the consequent real-time update of the best route suggested. In this paper, an architecture is proposed for the management of dynamic path planning and limitations of traditional search algorithms in these kinds of applications discussed. A variant of the proposed approach is consequently presented, based on the joint use of virus-evolutionary genetic algorithms for real-time route planning and traffic forecasting.
An Integrated architecture for Infomobility Services (Advantages of Genetic Algorithms in Real-Time Route Planning)
C De Castro;B M Masini;
2010
Abstract
In the field of Intelligent Transportation Systems, a key role is played by efficient route planning services. Such systems have been evolving rapidly, but they still have some restricting drawbacks, such as the lack of a full support of real-time traffic monitoring and the consequent real-time update of the best route suggested. In this paper, an architecture is proposed for the management of dynamic path planning and limitations of traditional search algorithms in these kinds of applications discussed. A variant of the proposed approach is consequently presented, based on the joint use of virus-evolutionary genetic algorithms for real-time route planning and traffic forecasting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.